Tag: GIS-Framework

Some modules are less concerned with specializing in one geospatial field than with trying to bring the various fields together and serve as a sort of all-purpose GIS framework that programmers can use for everyday tasks.

PyGeoprocessing is a Python/Cython based library that provides a set of commonly used raster, vector, and hydrological operations for GIS processing. Similar functionality can be found in ArcGIS/QGIS raster algebra, ArcGIS zonal statistics, and ArcGIS/GRASS/TauDEM hydrological routing routines.

PyGeoprocessing was developed at the Natural Capital Project to create a programmable, open source, and free GIS processing library to support the ecosystem service software InVEST. PyGeoprocessing’s design prioritizes computation and memory efficient runtimes, easy installation and cross compatibility with other open source and proprietary software licenses, and a simplified set of orthogonal GIS processing routines that interact with GIS data via filename. Specifically the functionally provided by PyGeoprocessing includes

GeoPandas is an open source project to make working with geospatial data in python easier. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely.

Depends on: Numpy, Pandas, Shapely, Fiona, six

Optional extensions: GeoPy, Psycopg2, Matplotlib, Descartes, PySAL

Python versions: 2.6, 2.7, 3.2+

OS Platforms: N/A

Installation:

Pip

The goals of Karta is to expose a simple and fast framework for spatial analysis. Karta serves as a Leatherman for geographic analyses. It provides simple and clean vector and raster data types, a selection of geographical analysis methods, and the ability to read and write several formats, including GeoJSON, shapefiles, and ESRI ASCII.